JMIR Medical Informatics (Jun 2024)

Data Flow Construction and Quality Evaluation of Electronic Source Data in Clinical Trials: Pilot Study Based on Hospital Electronic Medical Records in China

  • Yannan Yuan,
  • Yun Mei,
  • Shuhua Zhao,
  • Shenglong Dai,
  • Xiaohong Liu,
  • Xiaojing Sun,
  • Zhiying Fu,
  • Liheng Zhou,
  • Jie Ai,
  • Liheng Ma,
  • Min Jiang

DOI
https://doi.org/10.2196/52934
Journal volume & issue
Vol. 12
pp. e52934 – e52934

Abstract

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Abstract BackgroundThe traditional clinical trial data collection process requires a clinical research coordinator who is authorized by the investigators to read from the hospital’s electronic medical record. Using electronic source data opens a new path to extract patients’ data from electronic health records (EHRs) and transfer them directly to an electronic data capture (EDC) system; this method is often referred to as eSource. eSource technology in a clinical trial data flow can improve data quality without compromising timeliness. At the same time, improved data collection efficiency reduces clinical trial costs. ObjectiveThis study aims to explore how to extract clinical trial–related data from hospital EHR systems, transform the data into a format required by the EDC system, and transfer it into sponsors’ environments, and to evaluate the transferred data sets to validate the availability, completeness, and accuracy of building an eSource dataflow. MethodsA prospective clinical trial study registered on the Drug Clinical Trial Registration and Information Disclosure Platform was selected, and the following data modules were extracted from the structured data of 4 case report forms: demographics, vital signs, local laboratory data, and concomitant medications. The extracted data was mapped and transformed, deidentified, and transferred to the sponsor’s environment. Data validation was performed based on availability, completeness, and accuracy. ResultsIn a secure and controlled data environment, clinical trial data was successfully transferred from a hospital EHR to the sponsor’s environment with 100% transcriptional accuracy, but the availability and completeness of the data could be improved. ConclusionsData availability was low due to some required fields in the EDC system not being available directly in the EHR. Some data is also still in an unstructured or paper-based format. The top-level design of the eSource technology and the construction of hospital electronic data standards should help lay a foundation for a full electronic data flow from EHRs to EDC systems in the future.